Browse Articles

Elevated lipocalin-2, matrix matalloproteinase-9 and mmp-9/lcn-2 complex serum levels in hospitalized infants with severe bronchiolitis

Correction: One-year survival after critical care as a decision basis for advance care directives in general medicine: Real word data analysis of 149,144 patients

How nanobots are accelerating cancer-targeting therapies

Impact of talent cultivation model for industry education integration in vocational education by artificial intelligence and BPNN

Identification of natural Zika virus peptides presented on the surface of paediatric brain tumour cells by HLA class I

Despite decades of research, survival from brain cancer has scarcely improved and is drastically lower than that of other cancers. Novel therapies, such as immunotherapy, hold great promise for treating brain tumours and are desperately needed. Zika virus (ZIKV) infects and kills aggressive cancer cells with stem-like properties (CSCs) from both paediatric and adult brain tumours. Whilst T cell recruitment into ZIKV-infected brain tumours is becoming well documented, the specific mechanisms through which they are activated are poorly understood. We address this by employing a combined global proteome and immunopeptidome mass spectrometry approach to describe, for the first time, human leukocyte antigen (HLA) presentation of ZIKV peptides on the surface of infected brain tumour cells. We first show that antigen processing and presentation by HLA class I (HLA-I) is the top enriched immune response pathway in the global proteome of aggressive paediatric USP7-ATRT brain tumour cells following ZIKV infection. We identify USP7-ATRT cells as a desirable immunopeptidome model as they express the globally common HLA-A allotype (A*02:01). We predict the majority of our 19 identified ZIKV peptides to strongly bind and be presented by HLA-A*02:01. We observe a trend between immunopeptide presentation and cellular ZIKV protein abundance, with nearly half of the peptides arising from the most abundant viral protein; non-structural protein 3 (NS3). We show the ZIKV NS3 helicase domain to be a particularly rich source of peptides. Finally, we verify that the 19 ZIKV peptides identified here are not predicted to mimic peptides of the human proteome. The ZIKV peptides we identify here are novel targets for immunotherapy, and our findings provide potential insight into the efficacious cytotoxic T cell response that oncolytic ZIKV virotherapy can induce against brain tumours.

Transitions in dynamical regime and neural mode during perceptual decisions

Abstract Perceptual decision-making is thought to be mediated by neuronal networks with attractor dynamics 1,2 . However, the dynamics underlying the complex neuronal responses during decision-making remain unclear. Here we use simultaneous recordings of hundreds of neurons, combined with an unsupervised, deep-learning-based method, to discover decision-related neural dynamics in the rat frontal cortex and striatum as animals accumulate pulsatile auditory evidence. We found that trajectories evolved along two sequential regimes: an initial phase dominated by sensory inputs, followed by a phase dominated by autonomous dynamics, with the flow direction (that is, neural mode) largely orthogonal to that in the first regime. We propose that this transition marks the moment of decision commitment, that is, the time when the animal makes up its mind. To test this, we developed a simplified model of the dynamics to estimate a putative neurally inferred time of commitment (nTc) for each trial. This model captures diverse single-neuron temporal profiles, such as ramping and stepping 3,4 . The estimated nTc values were not time locked to stimulus or response timing but instead varied broadly across trials. If nTc marks commitment, evidence before this point should affect the decision, whereas evidence afterwards should not. Behavioural analysis aligned to nTc confirmed this prediction. Our findings show that decision commitment involves a rapid, coordinated transition in dynamical regime and neural mode and suggest that nTc offers a useful neural marker for studying rapid changes in internal brain state.

Identification of factors associated with foreign substance contamination in restaurant food

Using fuzzy logic and mathematical models to predict the financial efficiency of industrial enterprises

The frequent development and unpredictable, dynamic nature of industrial enterprises require an effective financial efficiency detection process. The prediction process uses a large volume of information to identify the details of resources and operational performance in industrial applications. Traditional statistical techniques like regression analysis, decision tree, and machine learning approaches significantly improve prediction efficiency. However, the existing methods face uncertainty, robustness, and scalability issues when exploring high-dimensional data. The research difficulties are addressed by integrating the Fuzzy logic and mathematical model called the FuzzyMath approach. The FuzzyMath concept understands the industrial economic details and predicts financial performance with maximum recognition accuracy. The collected inputs are explored using fuzzy systems that use the multivariate and salp optimization algorithm at every step to improve the overall system efficiency. The optimized membership function, fuzzy rule, and defuzzification process minimize the computation difficulties and can handle the uncertainty issues effectively. Thus, the FuzzyMath-based created rules ensure 99.23% accuracy while predicting financial efficiency in industrial applications.

Eco-friendly micellar HPLC for metformin and bisoprolol analysis in diverse matrices with a green and blueness perspective on drug purity and safety

Abstract Green analytical chemistry is an innovative approach to making analytical experiments more environmentally friendly, safer for humans, and less toxic to the environment by utilizing eco-friendly reagents and chemicals. Diabetics are twice as likely to experience hypertension compared to nondiabetics. Individuals with both conditions face a significantly increased risk of early microvascular and macrovascular complications. Regular monitoring helps ensure the drug concentration remains within the therapeutic range, maximizing its effectiveness. Herein, a high-performance liquid chromatographic (HPLC) method is provided to evaluate and isolate the studied drugs in the presence of their toxic impurities. The study involves the simultaneous administration of two crucial drugs: the antidiabetic metformin and the antihypertensive bisoprolol. We have investigated their pure form in spiked human plasma, as well as their interaction while their possible toxic impurities are present as melamine and cyanoguanidine. The optimal conditions were achieved using a mobile phase consisting of 0.1 M SDS, 0.1% ortho-phosphoric acid in water, and 10% isopropanol at a flow rate of 1.0 mL/min. The pH was adjusted to 5.0 using triethylamine, and the column temperature was maintained at 25 °C on a symmetry C18 column (Kinetex 1.7µ C18 100A, 2.1-mm × 50-mm), with detection at 230 nm. Following the International Conference of Harmonization guideline, the method was successfully validated within the linearity range of 1–25 µg/mL for metformin and bisoprolol. Notably, the LOQ was determined to be 0.92 µg/mL for metformin and 0.54 µg/mL for bisoprolol. The established method epitomizes accuracy, cost-effectiveness, selectivity, and reproducibility. The evaluation of the suggested approaches’ level of greenness was meticulously conducted using a variety of assessments, including the Analytical eco-scale system, the Modified Green Analytical Procedure Index (MoGAPI), The Analytical Green Star Area (AGSA), Blueness evaluation using BAGI tools, Carbon footprint (CaFRI), Click Analytical Chemistry Index (CACI) and White analytical chemistry (WAC).

Targeting MERTK tyrosine kinase: Virtual screening and molecular dynamics insights for anti-cancer drug development

Global public health facing serious challenges due to the incidence of cancer and the growth of treatment resistance. Mer-tyrosine kinase plays a crucial role in cell biology and correlated with many cancers such as Epithelial ovarian cancer, liver cancer, breast cancer, Metastatic melanoma, and Acute myeloid leukemia (AML). Hence the identification of novel drug for MERTK protein is extreme important. In this research, we used computational techniques, molecular operating environment (MOE 2015) for virtual screening with drug like natural compounds library. We used known compound UNC2025 as positive control and one million compounds was retrieved from different databases (OTAVA, ZINC, ChEMBL) and docked with MERTK protein. Out of million compounds the 4 top hit inhibitors chosen from docking were further screened for ADMET profiling confirming their compliance with drug designing and toxicological principle and subjected to molecular dynamic (MD) simulation and MM-PBSA analysis. The results of these analyses showed that only four compounds that make strong interactions with MERTK protein via highest binding affinity hydrogen bond and hydrophobic contacts (lig1, lig2, lig3, lig4). The computed binding affinity ranges from –22.977 to –18.707 kcal/mol. The increased helix and reduced β–sheet contents in MERTK on the binding of top hit candidates depicted the higher structural stability of MERTK, rather than MERTK alone and MERTK–UNC2025. The study finds critical residues which serve a vital part in binding with the inhibitor and the active site of the MERTK protein, i.e. , Phe598, Gly599, Lys619, Arg629, Glu633, Glu637, Arg722, Asp723, Arg727, Asp741, Gly743, Leu744, Lys746, Arg758, Ala760, and Lys761 through decomposed binding free energy analysis. This study focuses on the pursuit of several MERTK protein targets, which could have consequences for the development of novel therapeutics for various cancers.

Wired for growth: neuron–tumour signalling in the lung and brain increases growth of a hard-to-treat cancer

Integrated multiobjective optimization of RFSSW parameters for AA2024-T3 using ANOVA machine learning and NSGA II

Female sexual agency and frequent extra-pair copulations, but no extra-pair paternity, in Nazca boobies (Sula granti)

Extra-pair copulations (EPCs) are the poorly known antecedents of extra-pair fertilizations (EPFs) in birds. EPFs occur in most bird species that have been examined, but sexual conflict will generally reward females hiding their EPCs from males attempting to protect their paternity. EPCs will be difficult for researchers to document, and necessarily underestimated, in that case. We measured EPC behaviors and EPF frequency in a colonial seabird, the Nazca booby Sula granti , in which all copulations occur in a visually open setting with numerous possible copulatory partners readily available. Females are larger and more physically powerful than males, and are the numerically limiting sex, perhaps limiting options for males to control females. We found that all copulations were voluntary, and females’ sexual activities were wholly unconstrained by male coercion. Most females had multiple copulatory partners in the weeks preceding egg-laying. Despite the commonness of EPC, EPFs did not occur. The different schedules of EPC and within-pair copulation (WPC) provided a sufficient explanation for this outcome: during the ovulation window days before laying, WPC rate increased and EPC rate approached zero. To our knowledge, this is the first robust evidence of complete sexual agency in a female bird aside from lek-mating species, contributing a valuable exemplar to the literature on sexual conflict over reproduction.

Reduced postural stability in men and women aged 55–65 following 14 days of head-down bed rest

Abstract Aging and head-down bed rest (HDBR) decrease postural stability. Chances of being bedridden increase with age, but HDBR studies usually focus on young men. Here, we evaluate the impact of HDBR on postural stability among late middle-aged individuals. Twenty-two healthy participants (55–65 years old, 11 women) were exposed to 14-day HDBR. Eleven participants performed daily exercise. Static posturography data were collected before, 5 h after, and 4 weeks after HDBR. No time×group or time×sex effects were observed, but women had lower postural stability. With eyes open, the root mean square of the center of pressure was larger immediately after HDBR only in the medio-lateral axis (median [interquartile range]: +53% [+ 15%; +129%], p  = 0.002). The mean velocity was increased on both axes (+ 20% [+ 8%; +46%] for medio-lateral and + 19% [+ 13%; +36%] for antero-posterior, both p  < 0.001). The complexity features and the critical time were left unchanged. The effects of HDBR were more visible in the eyes open condition and the deconditioning was reversible after four weeks. 14-day HDBR decreased postural stability in individuals aged 55–65, with no impact of the chosen countermeasure. While the deconditioning was equivalent to two decades of aging for some features, additional research is required to determine whether age was an aggravating factor.

ALGR: A multi-purpose agricultural landscape generator in R

Agricultural and ecological modelers commonly use maps as input for spatially explicit simulations. While real world maps are often used, they are limited by being static objects, therefore making it difficult to assess how patterns within the landscape contribute to ecological processes. Agricultural landscape generators (ALG) are a useful tool for simulating maps in a more flexible way. They can increase robustness of models that rely on landscape maps as input, they allow modelers to give spatial representation to non-spatial models, and they are a useful tool for recreating spatial patterns in agricultural-dominated landscapes. A limitation of previous ALGs is that they have rarely been designed for general use (non-open source software, not written in R, and designed for specific projects). Furthermore, they are typically either extremely general and thus oversimplified or have a high specificity for particular use cases. ALGR bridges this gap by providing a general-purpose, dynamic landscape generator that balances structural realism with adaptability. ALGR generates agricultural landscapes with a three-step approach: first, outlining potential space, second, field placement inside of that space, and third, enrichment of the landscape with information. This stepwise approach ensures that ALGR generates landscapes with realistic spatial patterns while remaining adaptable to diverse regions and applications. It is the first ALG that is specifically designed to allow a simple integration within the R programming environment and the r-spatial package environment. ALGR is designed as a general-purpose generator, which is simple to use and facilitates an easy integration in modelling workflow. We present several examples of workflows using ALGR , to demonstrate its usefulness. Our examples include: 1) simulating different land use shares, 2) parameter tuning of ALGR to recreate real world landscape, patterns 3) spatially distributing crop portfolios, and 4) using real-world maps as a basis for field placement.

Explainable attention-based deep learning for classification and interpretation of heart murmurs using phonocardiograms

Epigenetic regulation of inflammation in post-operative organ dysfunction: A scoping review protocol

Introduction The inflammatory response to surgery is complex, dynamic and exhibits variability in magnitude and duration among patients undergoing similar operations. Dysregulated inflammation is associated with post-operative complications such as organ dysfunction, particularly after major surgery. Epigenetic modifications enhance (or suppress) selective gene transcription without altering DNA sequences, effectively regulating gene expression. Several studies have investigated epigenetic regulation of the immune system in the context of surgery, often studying organ-specific dysfunction. Objectives We propose a novel scoping review protocol to collate and synthesise existing studies investigating epigenetic regulation of post-operative inflammation, as a key mechanism of post-operative organ dysfunction and complications. We will map knowledge gaps to inform future research in this emerging field. Methods and analysis This scoping review protocol has been created following the Joanna Brigg’s Institute (JBI) updated guidelines for conducting scoping reviews. The protocol has been further examined alongside the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) extension for Scoping Reviews (PRISMA-ScR) checklist and is registered on Open Science Framework (doi.org/10.17605/OSF.IO/CE8FB). Published human studies from 1946 to the present will be considered. Studies will include patients undergoing surgery, where epigenetic regulation of the immune system is investigated alongside assessment of organ dysfunction or complications. Searches will be conducted using Medline (via OVID) and Embase. Two reviewers will independently screen titles, abstracts and full texts of studies meeting the inclusion criteria. Following study screening, a customised data extraction form will collect study information related to the review questions and inclusion criteria (population, concept, context). Results will be presented by diagrammatic mapping of studies and tabular representation of findings.

Building wet planets through high-pressure magma–hydrogen reactions

Abstract Close-in transiting sub-Neptunes are abundant in our Galaxy 1 . Planetary interior models based on their observed radius–mass relationship suggest that sub-Neptunes contain a discernible amount of either hydrogen (dry planets) or water (wet planets) blanketing a core composed of rocks and metal 2 . Water-rich sub-Neptunes have been believed to form farther from the star and then migrate inwards to their present orbits 3 . Here we report experimental evidence of reactions between warm, dense hydrogen fluid and silicate melt that release silicon from the magma to form alloys and hydrides at high pressures. We found that oxygen liberated from the silicate melt reacts with hydrogen, producing an appreciable amount of water up to a few tens of weight per cent, which is much greater than previously predicted based on low-pressure ideal gas extrapolation 4,5 . Consequently, these reactions can generate a spectrum of water contents in hydrogen-rich planets, with the potential to reach water-rich compositions for some sub-Neptunes, implying an evolutionary relationship between hydrogen-rich and water-rich planets. Therefore, detection of a large amount of water in exoplanet atmospheres may not be the optimal evidence for planet migration in the protoplanetary disk, calling into question the assumed link between composition and planet formation location.

In-depth behavioral characterization of a rat model of Schaaf-Yang syndrome

Abstract Schaaf-Yang syndrome (SYS, OMIM #615547) is a rare neurodevelopmental disorder caused by truncating variants in the maternally imprinted MAGEL2 gene. It is characterized by intellectual disability, autism spectrum disorder, joint contractures, and feeding difficulties. Although MAGEL2 is deleted in most cases of Prader-Willi syndrome (PWS, OMIM #176270), SYS presents with more severe symptoms, suggesting pathogenic effects of truncated MAGEL2 beyond a mere loss of function. This study expands the behavioral characterization of a novel rat model (“ Magel2 Pmut rats”) which carries a truncating mutation on the paternal allele of Magel2 , offering greater construct validity for SYS than previous animal models with Magel2 deletion. While an initial study provided first insights, key domains within the behavioral phenotype of the model remained unexplored. Our comprehensive behavioral analysis, including home-cage monitoring, ultrasonic vocalization analysis, and precise gait assessment, identified several phenotypic alterations potentially relevant to the study of SYS. Magel2 Pmut rats exhibited abnormal feeding behavior, changes in early social communication, alterations in gait, aberrant behavior in the elevated plus maze, and delayed decision-making. Additionally, we confirmed that Magel2 Pmut rats show phenotypes of abnormal social interaction. These results may reflect core symptoms seen in SYS, underscoring the value of this model for preclinical research on pathophysiology and therapeutics.

Partial blue light blocking glasses at night advanced sleep phase and reduced daytime irritability, disruptive behavior and improved morning mood, but did not alter salivary melatonin secretion in Japanese male schoolchildren

In modern society, delayed sleep patterns among schoolchildren present challenges to academic attendance and performance. The impact of nighttime light exposure, especially blue wavelength light, on sleep delay has long been acknowledged. We investigated the effects of using partial blue light blocking glasses (JINS Screen Lens Heavy [40% cut]) on salivary melatonin levels, sleep patterns, sleep circadian phase, and daytime behavior in 39 male schoolchildren aged 10–12 who regularly wear glasses for myopia. Participants alternated between blue light blocking and standard clear lens glasses, both providing vision correction, for three hours before their habitual bedtime. The study was conducted over five weeks using a crossover design with two-week glasses-wearing sessions and a one-week washout interval between conditions. While blue light blocking glasses did not influence salivary melatonin levels, they significantly advanced the sleep phase (bedtime: 22.03 ± 0.08h vs. 22.13 ± 0.09h, p = 0.040, sleep onset: 22.26 ± 0.08h vs. 22.36 ± 0.10h, p = 0.041). The effects were more pronounced in the second week and accompanied by reduced irritability and disruptive behavior during daytime. Our results suggest that wearing blue light blocking glasses before bedtime may advance the sleep phase and improve daytime behavior in schoolchildren under real-world living conditions, warranting further mechanistic investigation.